Machine Learning for Biometrics

Concepts, Algorithms and Applications
Erscheinungsjahr 2022
ISBN: 978-0-323-85209-8
Verlag: William Andrew Publishing

Buch, Englisch, 264 Seiten, Format (B × H): 152 mm x 229 mm, Gewicht: 430 g

Machine Learning for Biometrics: Concepts, Algorithms and Applications highlights the fundamental concepts of machine learning, processing and analyzing data from biometrics and provides a review of intelligent and cognitive learning tools which can be adopted in this direction. Each chapter of the volume is supported by real-life case studies, illustrative examples and video demonstrations. The book elucidates various biometric concepts, algorithms and applications with machine intelligence solutions, providing guidance on best practices for new technologies such as e-health solutions, Data science, Cloud computing, and Internet of Things, etc.

In each section, different machine learning concepts and algorithms are used, such as different object detection techniques, image enhancement techniques, both global and local feature extraction techniques, and classifiers those are commonly used data science techniques. These biometrics techniques can be used as tools in Cloud computing, Mobile computing, IOT based applications, and e-health care systems for secure login, device access control, personal recognition and surveillance.

Zielgruppe

<p>Primary: Faculty members, graduate/master degree students and research scholars, practitioners, developers, engineers, etc. from Computer Science & Engineering, Information Technology, Electronics Engineering, Electrical Engineering, Electrical and Electronics Engineering disciplines. </p> <p>Secondary: Biometrics, Computer vision, Data Science, Cloud computing, Cyber Security, e-Health monitoring systems, Internet of Things security</p>

Autoren/Hrsg.

Sarangi, Partha Pratim

Panda, Madhumita

Mishra, Subhashree

Mishra, Bhabani Shankar Prasad

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Mustererkennung, Biometrik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen

Inhaltsverzeichnis

1. Fundamentals of Biometrics and reviews of different biometrics and multimodal biometrics 2. Detection techniques of different biometric traits 3. Preprocessing using Machine learning approaches 4. Feature extraction and selection using Machine learning approaches 5. Recognition (Verification and Identification) techniques 6. Behavioral biometrics 7. Biometrics in Forensic Identification 8. Biometric cryptography (Bio-Cryptography) 9. Multimodal Biometrics 10. Security Applications

Über Autor(innen)

Panda, Madhumita
Ms. Madhumita Panda, is working as Assistant Professor in Master in Computer Applications at Seemanta Engineering College, Jharpokharia, Odisha. She has received his M.Tech in Computer Science from NIT Rourkela and continuing her Ph.D. from North Orissa University, Baripada, Odisha. Her current research interests include Pattern Recognition, Soft computing, Biometrics, Software Engineering. She has already published 2 book chapters and about 10 research papers in refereed journals and conferences.

Sarangi, Partha Pratim
Dr. Partha Pratim Sarangi, is working as Professor in Computer Sc. & Engineering at Seemanta Engineering College, Jharpokharia, Odisha, INDIA. He has received his Ph.D. in Computer Science from KIIT University, Bhubaneswar, Odisha. His current research interests include Pattern Recognition, Soft computing, Biometrics, Computer Vision, and Data Science. He has already published about 22 research papers in refereed journals and conferences.

Mishra, Bhabani Shankar Prasad
Dr. Bhabani Shankar Prasad Mishra born in Talcher, Odisha, India in 1981. He received the B.Tech. in Computer Science and Engineering from Biju Pattanaik Technical University, Odisha in 2003, M.Tech. degree in Computer Science and Engineering from the KIIT University, in 2003, Ph.D. degree in Computer Science from F.M.University, Balasore,Odisha, India, in 2011 and Post Doc in 2013 from Soft Computing Laboratory, Yansei University, South Korea.

Currently he is working as an Associate Professor and Dean at School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India. His research interest includes Pattern Reorganization, Data Mining, Soft Computing, Big Data and Machine Learning. He has published more than 80 research articles in reputed Journal and Conferences, has edited more than five books of current importance. Under his guidance, 2 PhD scholars are already been awarded;

Dr. Mishra was the recipient of the Gold Medal and Silver Medal during his M.Tech for the best Post Graduate in the University. He is the member of different technical bodies ISTE, CSI and IET.

Mishra, Subhashree
Dr. Subhashree Mishra, is working as an Assistant Professor in School of Electronics Engineering at KIIT University, Bhubaneswar. She has completed her Master and PhD from KIIT University respectively. Her research interest includes Machine Learning, Communication Engineering, Image Processing and Soft Computing. She has published around 15 research articles and 4 Book chapters in referred journals and conferences. Currently she is guiding 2 PhD scholars.